Tracking Parkinson's disease (PD) symptom progression often uses the unified Parkinson's disease rating scale (UPDRS) that requires the patient's presence in clinic, and time-consuming physical examinations by trained medical staff. Thus, symptom monitoring is costly and logistically inconvenient for patient and clinical staff alike, also hindering recruitment for future large-scale clinical trials. Here, for the first time, we demonstrate rapid, remote replication of UPDRS assessment with clinically useful accuracy (about 7.5 UPDRS points difference from the clinicians' estimates), using only simple, self-administered, and noninvasive speech tests. We characterize speech with signal processing algorithms, extracting clinically useful features of average PD progression. Subsequently, we select the most parsimonious model with a robust feature selection algorithm, and statistically map the selected subset of features to UPDRS using linear and nonlinear regression techniques that include classical least squares and nonparametric classification and regression trees. We verify our findings on the largest database of PD speech in existence (~6000 recordings from 42 PD patients, recruited to a six-month, multicenter trial). These findings support the feasibility of frequent, remote, and accurate UPDRS tracking. This technology could play a key part in telemonitoring frameworks that enable large-scale clinical trials into novel PD treatments.

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Accurate Telemonitoring of Parkinson's Disease Progression by Noninvasive Speech Tests

Sex hormones and the female voice.

An assessment of vocal impairment is presented for separating healthy people from persons with early untreated Parkinson’s disease (PD). This study’s main purpose was to (a) determine whether voice and speech disorder are present from early stages of PD before starting dopaminergic pharmacotherapy, (b) ascertain the specific characteristics of the PD-related vocal impairment, (c) identify PD-related acoustic signatures for the major part of traditional clinically used measurement methods with respect to their automatic assessment, and (d) design new automatic measurement methods of articulation. The varied speech data were collected from 46 Czech native speakers, 23 with PD. Subsequently, 19 representative measurements were pre-selected, and Wald sequential analysis was then applied to assess the efficiency of each measure and the extent of vocal impairment of each subject. It was found that measurement of the fundamental frequency variations applied to two selected tasks was the best method for separating healthy from PD subjects. On the basis of objective acoustic measures, statistical decision-making theory, and validation from practicing speech therapists, it has been demonstrated that 78% of early untreated PD subjects indicate some form of vocal impairment. The speech defects thus uncovered differ individually in various characteristics including phonation, articulation, and prosody.

https://www.utdallas.edu/~hynek/citing_papers/Rusz_Quantitative%20acoustic%20measurements%20for%20characterization%20of%20speech%20and%20voice%20disorders%20in%20early%20untreated%20Parkinson's%20disease.pdf

Quantitative acoustic measurements for characterization of speech and voice disorders in early untreated Parkinson’s disease

Background: acoustic and perceptual changes to speech in Parkinson’s disease (PD) have been widely studied. Little empirical evidence exists concerning the individual’s own perception of changes, the impact these have on their life and coping strategies to deal with them. 

Objective: to establish if, and how, changes in communication impact on the lives of people with PD. 

Design: in-depth interviews with qualitative analysis of content. 

Setting: community. 

Subjects: twenty-three men and 14 women with PD. 

Methods: participants were purposively sampled to give a mix of men, women, family circumstances, stage and duration of PD and severity of speech symptoms. Individuals were interviewed at home. Interviews were transcribed. Emergent themes were identified and fed back to participants for confirmation and clarification. 

Results: participants identified changes to voice and articulation. Language changes featured prominently. Four impact themes: (i) interaction with others, (ii) problems with conversations, (iii) feelings about intelligibility and (iv) voice; and four corresponding coping themes (a) helping others understand, (b) managing conversations, (c) monitoring and adjusting and (d) physical strategies emerged. Of main concern was not the nature of speech-voice-language changes, but how these affected self-concept, participation inside and outside the family and family dynamics. Individuals employed a range of fluid coping strategies moving from background withdrawal to foreground striving strategies. 

Conclusions: speech and language changes in PD impact upon individual and family life long before frank impairment of intelligibility is apparent. The role of early referral to speech and language therapy is therefore worthy of detailed investigation.

Life with communication changes in Parkinson’s disease

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

/pdf/nonlinear-speech-analysis-algorithms-mapped-to-a-standard-nluu7omn19.pdf

Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

This study examined the acoustic and perceptual voice characteristics of patients with Parkinson's disease according to disease severity. The perceptual and acoustic voice characteristics of 30 patients with early stage PD and 30 patients with later stage PD were compared with data from 30 normal control subjects. Voice recordings consisted of prolongation of the vowel /a/, scale singing, and a 1-min monologue. In comparison with controls and previously published normative data, both early and later stage PD patients' voices were characterized perceptually by limited pitch and loudness variability, breathiness, harshness and reduced loudness. High modal pitch levels also characterized the voices of males in both early and later stages of PD. Acoustically, the voices of both groups of PD patients demonstrated lower mean intensity levels and reduced maximum phonational frequency ranges in comparison with normative data. Although less clear, the present data also suggested that the PD patients' voices were characterized by excess jitter, a high-speaking fundamental frequency for males and a reduced fundamental frequency variability for females. While several of these voice features did not appear to deteriorate with disease progression (i.e. harshness, high modal pitch and speaking fundamental frequency in males, fundamental frequency variability in females, low intensity and jitter), breathiness, monopitch and monoloudness, low loudness and reduced maximum phonational frequency range were all worse in the later stages of PD. Tremor was the sole voice feature which was associated only with later stage PD.

Debbie J. Phyland

Papers

Voice characteristics in the progression of Parkinson’s disease

Effects of laryngeal endoscopy on the vocal performanceof young adult females with normal voices